Real data: PSA, ECB, SWS, DOLE wage boards, Department of Agriculture · KPIs show — · same pages, measures and slicers as the Power BI report
Real GDP growth fell from —% to —% in a year. A weaker peso makes imported rice and fuel cost more, and ₱1 from 2018 now buys ₱— worth of goods. Use the date slicer to zoom the charts.
Real GDP, % vs same quarter a year earlier · PSA
Monthly average · higher = stronger dollar · ECB · dashed: current month to date (provisional, ECB daily rates), then 12-month trend projected from the latest daily rate to year end, shaded 95% range
% vs a year earlier · shaded: BSP 2–4% target · PSA
After the import tariff was cut, retail rice fell to ₱—/kg. Imports were then suspended and a new tariff started, and prices jumped back to ₱—. Hover a chart for monthly values.
Regular-milled, ₱ per kg · numbered lines: policy changes · PSA
NCR daily minimum wage ÷ NCR rice price · DOLE, PSA
SWS finds —% of families went hungry in the latest survey. It never fell below —% even when rice was cheapest. Click a bar to compare it with the latest survey.
% of families, per SWS survey · click a bar
— of — regions have rice inflation above the national rate. Pick an island group, then click a bar or a row: the cards switch to that region, like cross-filtering in Power BI.
% vs a year earlier · red: above national · dashed: national · PSA
Latest month · click a header to sort, a row to select
| Region | Rice ₱/kg | Price change % | Rice infl. % |
|---|
This dashboard and the Power BI report come from the same pipeline. Each stage has its own file in the project.
Pulls PSA OpenSTAT and ECB data through their APIs, adds SWS, wage-order and policy figures with source links, and saves one raw Excel workbook.
Unpivots month columns, turns PSA's “.” placeholders into nulls, parses dates, sets types, and joins PSA's two region-naming styles.
Fact tables for prices, inflation, FX, GDP and hunger, linked to a Calendar and a Region dimension.
Measures for latest vs year-ago, peso weakening, months above target, kg of rice per wage, regional gaps.
Story pages with slicers, cross-highlighting and drill-through, mirrored in this web dashboard.
Checks that every DAX column and measure exists, compares cards with expected values, then shares the .pbix.